A Better Index of Body Adiposity

Total Page:16

File Type:pdf, Size:1020Kb

A Better Index of Body Adiposity University of Pennsylvania ScholarlyCommons Departmental Papers (Vet) School of Veterinary Medicine 5-2011 A Better Index of Body Adiposity Richard N. Bergman Darko Stefanovski University of Pennsylvania, [email protected] Thomas A. Buchanan Anne E. Sumner James C. Reynolds See next page for additional authors Follow this and additional works at: https://repository.upenn.edu/vet_papers Part of the Disease Modeling Commons Recommended Citation Bergman, R. N., Stefanovski, D., Buchanan, T. A., Sumner, A. E., Reynolds, J. C., Sebring, N. G., Xiang, A. H., & Watanabe, R. M. (2011). A Better Index of Body Adiposity. Obesity: A Research Journal, 19 (5), 1083-1089. http://dx.doi.org/10.1038/oby.2011.38 At the time of publication, author Darko Stefanovski was affiliated with theeck K School of Medicine at the University of Southern California. Currently, he is a faculty member at the University of Pennsylvania's School of Veterinary Medicine. This paper is posted at ScholarlyCommons. https://repository.upenn.edu/vet_papers/137 For more information, please contact [email protected]. A Better Index of Body Adiposity Abstract Obesity is a growing problem in the United States and throughout the world. It is a risk factor for many chronic diseases. The BMI has been used to assess body fat for almost 200 years. BMI is known to be of limited accuracy, and is different for males and females with similar %body adiposity. Here, we define an alternative parameter, the body adiposity index (BAI = ((hip circumference)/((height)1.5)–18)). The BAI can be used to reflect %body fat for adult men and women of differing ethnicities without numerical correction. We used a population study, the “BetaGene” study, to develop the new index of body adiposity. %Body fat, as measured by the dual-energy X-ray absorptiometry (DXA), was used as a “gold standard” for validation. Hip circumference (R = 0.602) and height (R = −0.524) are strongly correlated with %body fat and therefore chosen as principal anthropometric measures on which we base BAI. The BAI measure was validated in the “Triglyceride and Cardiovascular Risk in African-Americans (TARA)” study of African Americans. Correlation between DXA-derived %adiposity and the BAI was R = 0.85 for TARA with a concordance of C_b = 0.95. BAI can be measured without weighing, which may render it useful in settings where measuring accurate body weight is problematic. In summary, we have defined a new parameter, the BAI, which can be calculated from hip circumference and height only. It can be used in the clinical setting even in remote locations with very limited access to reliable scales. The BAI estimates %adiposity directly. Disciplines Disease Modeling Comments At the time of publication, author Darko Stefanovski was affiliated with theeck K School of Medicine at the University of Southern California. Currently, he is a faculty member at the University of Pennsylvania's School of Veterinary Medicine. Author(s) Richard N. Bergman, Darko Stefanovski, Thomas A. Buchanan, Anne E. Sumner, James C. Reynolds, Nancy G. Sebring, Anny H. Xiang, and Richard M. Watanabe This journal article is available at ScholarlyCommons: https://repository.upenn.edu/vet_papers/137 A Better Index of Body Adiposity Richard N. Bergman1, Darko Stefanovski1, Thomas A. Buchanan2,3, Anne E. Sumner4, James C. Reynolds5, Nancy G. Sebring6, Anny H. Xiang7, and Richard M. Watanabe8 1Department of Physiology and Biophysics, Keck School of Medicine, University of Southern California, Los Angeles, California, USA 2Department of Medicine, Keck School of Medicine, University of Southern California, Los Angeles, California, USA 3Department of Ob/Gyn and Physiology and Biophysics, Keck School of Medicine, University of Southern California, Los Angeles, California, USA 4Clinical and Endocrinology Branch, National Institute of Diabetes and Digestive and Kidney Disease (NIDDK), National Institutes of Health, Bethesda, Maryland, USA 5Department of Radiology and Imaging Sciences, Nuclear Medicine, National Institutes of Health, Bethesda, Maryland, USA 6Nutrition, National Institutes of Health, Bethesda, Maryland, USA 7Department of Research and Evaluation, Kaiser Permanente Southern California Medical Group, Pasadena, California, USA 8Department of Preventive Medicine, Division of Biostatistics, Keck School of Medicine, University of Southern California, Los Angeles, California, USA Abstract Obesity is a growing problem in the United States and throughout the world. It is a risk factor for many chronic diseases. The BMI has been used to assess body fat for almost 200 years. BMI is known to be of limited accuracy, and is different for males and females with similar %body adiposity. Here, we define an alternative parameter, the body adiposity index (BAI = ((hip circumference)/((height)1.5) − 18)). The BAI can be used to reflect %body fat for adult men and women of differing ethnicities without numerical correction. We used a population study, the “BetaGene” study, to develop the new index of body adiposity. %Body fat, as measured by the dual-energy X-ray absorptiometry (DXA), was used as a “gold standard” for validation. Hip circumference (R = 0.602) and height (R = −0.524) are strongly correlated with %body fat and therefore chosen as principal anthropometric measures on which we base BAI. The BAI measure was validated in the “Triglyceride and Cardiovascular Risk in African-Americans (TARA)” study of African Americans. Correlation between DXA-derived %adiposity and the BAI was R = 0.85 for TARA with a concordance of C_b = 0.95. BAI can be measured without weighing, which may render it useful in settings where measuring accurate body weight is problematic. In summary, we have defined a new parameter, the BAI, which can be calculated from hip circumference and height only. It can be used in the clinical setting even in remote locations with very limited access to reliable scales. The BAI estimates %adiposity directly. Bergman et al. Page 2 INTRODUCTION Alarming increases in adiposity have been identified in the United States and in other affluent countries (1–3). Obesity is a risk factor for many diseases, including type 2 diabetes mellitus, cardiovascular disease, hypertension, and cancer (4,5). Worldwide increases in diabetes and other chronic diseases will cause great suffering, and overwhelm medical treatment systems. Thus, there have been heroic efforts to attempt to reverse the increase in obesity, although such reversal has proved intractable in many situations (6). It is important to target efforts to reduce adiposity for groups most at-risk for obesity-related chronic diseases. Various methods have been developed to assess adiposity. Underwater weighing and dual-energy X-ray absorption (DXA) are most accurate for quantifying body fat, and computed tomography scans and magnetic resonance imaging can assess body fat distribution. However, such technologically complex methods are too costly and time consuming to be applied routinely in clinical settings. Surrogate methods such as impedance analysis and skin-fold thickness can also be used, but are notoriously inaccurate (7,8). Other than simple measurement of body weight, the BMI is by far the most commonly applied approach to characterize obesity in individual subjects. This measure was introduced in the 19th century by Quetelet (9), who recognized that it is necessary to correct for differences in body size when comparing adiposity among patients. Because growth is linear, weight cannot increase as the cube of height, but as the square, and the human represents a cylinder more than a sphere. Quetelet’s index, renamed the BMI by Ancel Keys (10), is the ratio of weight to height squared. The BMI is now routinely applied to estimate body fat, not only in epidemiological studies, but also in clinical practice, despite warnings that it is not a very accurate measure of adiposity in individual patients (11). The BMI is particularly inaccurate in subjects with elevated lean body mass, such as athletes, and cannot be generalized among different ethnic groups (12,13). It is likely that individuals are often misdiagnosed as having inappropriate body fat due to variation in muscle mass, and that certain subjects with significant adiposity are overlooked. Determining adiposity in children is particularly difficult. In children, the most prevalent approach of determining body composition is to use BMI normalized by age (14). This in turn leads to complex mathematical calculations which require access to calculation software or the use of charts and tables which may not be available to those working in the health and nutrition field. Large cohorts are required to estimate the normalization factors that later are to be used by the practitioners. Furthermore, the BMI cannot be calculated in settings where accurate measures of body weight cannot be obtained (e.g., in fieldwork or in underdeveloped countries). METHODS AND PROCEDURES Identification of the index: The BetaGene study To define a measure of adiposity we initially queried a single, large study in which a variety of body measures were made. The “BetaGene” study was performed by three of the coauthors (T.A.B., R.M.W., and A.H.X.). Recruitment has been described in detail previously (15). Briefly, 1,733 subjects are Mexican American (Table 1, both parents and ≥3 grandparents Mexican or of Mexican descent) who are either probands with gestational diabetes mellitus (GDM) diagnosed within the previous 5 years (16) and their siblings and cousins, or probands with normal glucose levels in pregnancy in the past 5 years. All probands were identified from the patient populations at Los Angeles County/USC Medical Center, the Kaiser Permanente Southern California health plan membership, and OB/GYN clinics at local hospitals in Los Angeles. GDM probands were required to have glucose levels associated with poor pancreatic β-cell function and a high risk of diabetes when not Obesity (Silver Spring). Author manuscript; available in PMC 2012 February 8. Bergman et al. Page 3 pregnant (17), have no evidence of β-cell autoimmunity by GAD-65 testing, and have at least two siblings available for study.
Recommended publications
  • Discordance Between Body-Mass Index and Body Adiposity Index in the Classification of Weight Status of Elderly Patients With
    Journal of Clinical Medicine Article Discordance between Body-Mass Index and Body Adiposity Index in the Classification of Weight Status of Elderly Patients with Stable Coronary Artery Disease Bartosz Hudzik 1,2,* , Justyna Nowak 1, Janusz Szkodzinski 2, Aleksander Danikiewicz 3, Ilona Korzonek-Szlacheta 1 and Barbara Zubelewicz-Szkodzi ´nska 3,4 1 Department of Cardiovascular Disease Prevention, Department of Metabolic Disease Prevention, Faculty of Health Sciences, Medical University of Silesia, 41-900 Bytom, Poland; [email protected] (J.N.); [email protected] (I.K.-S.) 2 Third Department of Cardiology, Silesian Center for Heart Disease, Faculty of Medical Sciences, Medical University of Silesia, 41-800 Zabrze, Poland; [email protected] 3 Department of Nutrition-Related Disease Prevention, Department of Metabolic Disease Prevention, Faculty of Health Sciences, Medical University of Silesia, 41-900 Bytom, Poland; [email protected] (A.D.); [email protected] (B.Z.-S.) 4 Department of Endocrinology, District Hospital, 41-940 Piekary Sl´ ˛askie,Poland * Correspondence: [email protected]; Tel.: +48-32-3733619; Fax: +48-32-2732679 Abstract: Background and Aims: Body-mass index (BMI) is a popular method implemented to define weight status. However, describing obesity by BMI may result in inaccurate assessment of adiposity. Citation: Hudzik, B.; Nowak, J.; The Body Adiposity Index (BAI) is intended to be a directly validated method of estimating body Szkodzinski, J.; Danikiewicz, A.; fat percentage. We set out to compare body weight status assessment by BMI and BAI in a cohort Korzonek-Szlacheta, I.; of elderly patients with stable coronary artery disease (CAD).
    [Show full text]
  • Redalyc.BMI, Bmifat, BAI Or Baifels – Which Is the Best Adiposity Index for the Detection of Excess Weight?
    Nutrición Hospitalaria ISSN: 0212-1611 [email protected] Sociedad Española de Nutrición Parenteral y Enteral España Ramos Silva, Bruna; Savegnago Mialich, Mirele; Hoffman, Daniel J.; Jordao Junior, Alceu Afonso BMI, BMIfat, BAI or BAIFels – Which is the best adiposity index for the detection of excess weight? Nutrición Hospitalaria, vol. 34, núm. 2, marzo-abril, 2017, pp. 389-395 Sociedad Española de Nutrición Parenteral y Enteral Madrid, España Available in: http://www.redalyc.org/articulo.oa?id=309250505021 How to cite Complete issue Scientific Information System More information about this article Network of Scientific Journals from Latin America, the Caribbean, Spain and Portugal Journal's homepage in redalyc.org Non-profit academic project, developed under the open access initiative Nutr Hosp. 2017; 34(2):389-395 ISSN 0212-1611 - CODEN NUHOEQ S.V.R. 318 Nutrición Hospitalaria Trabajo Original Valoración nutricional BMI, BMIfat, BAI or BAIFels – Which is the best adiposity index for the detection of excess weight? Índice de masa corporal (IMC), IMC ajustado a la grasa, índice de adiposidad (IA) e IA ajustado (BaIFels). ¿Cuál es el mejor índice de adiposidad para detectar el exceso de peso? Bruna Ramos Silva 1, Mirele Savegnago Mialich 1, Daniel J. Hoffman 2 and Alceu Afonso Jordao Junior 1 1Department of Internal Medicine. Ribeirao Preto Medical School. University of Sao Paulo. Ribeirao Preto, SP. Brazil. 2Department of Nutritional Sciences. Rutgers University. New Brunswick, New Jersey. USA Abstract Objective: To compare the diagnostic performance of adiposity indeces body mass index (BMI), body mass index adjusted for fat mass (BMIfat), body adiposity index (BAI) and body adiposity index for the Fels Longitudinal Study sample (BAIFels) and the overweight detection in a sample of the Brazilian population.
    [Show full text]
  • Association of New Obesity Indices; Visceral Adiposity Index and Body Adiposity Index, with Metabolic Syndrome Parameters in Obese Patients with Or Without Type 2 Diabetes Mellitus
    620 Original article Association of new obesity indices; visceral adiposity index and body adiposity index, with metabolic syndrome parameters in obese patients with or without type 2 diabetes mellitus Nearmeen M. Rashad, George Emad Department of Internal Medicine, Faculty of Background Medicine, Zagazig University, Zagazig, Egypt Obesity is the cornerstone of metabolic syndrome (MetS); it is not possible to use Correspondence to Nearmeen M. Rashad, MD, BMI to differentiate between lean mass and fat mass. We aimed to investigate, for Department of Internal Medicine, Faculty of the first time, the possible association of new obesity indices; visceral adiposity Medicine, Zagazig University, 44519, Zagazig, index (VAI) and body adiposity index (BAI), with parameters of MetS in Egyptian Egypt. Tel: +20 122 424 8642; e-mails: [email protected], [email protected] obese patients. Patients and methods Received 3 January 2019 This was a case–control study that included unrelated 150 obese patients and 50 Accepted 6 February 2019 Published: 18 August 2020 healthy controls. Obese patients were then subdivided into two subgroups, nondiabetic patients (n=85) and 65 patients with type 2 diabetes mellitus. We The Egyptian Journal of Internal Medicine 2019, 31:620–628 measured the anthropometric measures; BMI, waist/hip ratio, waist/height ratio, BAI, and VAI. Results Among obese patients, we found significant positive correlations between parameters of MetS and obesity indices. Among obesity indiced, the highly significant positive correlations were found between VAI and parameters of MetS. After adjusting for the traditional risk factors, logistic regression analysis test found that the VAI value was the best predictor of type 2 diabetes mellitus in comparison with BMI and BAI.
    [Show full text]
  • Rev Bras Cineantropom Desempenho Hum Original Article DOI: Doi.Org/10.1590/1980-0037.2021V23e76348
    Rev Bras Cineantropom Desempenho Hum original article DOI: doi.org/10.1590/1980-0037.2021v23e76348 Body adiposity index and associated factors in workers of the furniture sector Índice de adiposidade corporal e fatores associados em trabalhadores do setor moveleiro Renata Aparecida Rodrigues de Oliveira1 https://orcid.org/0000-0002-5004-5253 Paulo Roberto dos Santos Amorim1 https://orcid.org/0000-0002-4327-9190 Braúlio Parma Baião2 https://orcid.org/0000-0002-0997-8457 Pedro Victor Santos Rodrigues de Oliveira2 https://orcid.org/0000-0002-6314-2562 João Carlos Bouzas Marins1 https://orcid.org/0000-0003-0727-3450 Abstract – Obesity represents one of the main cardiovascular risk factors with high preva- lence among the Brazilian population. The aim of this study was to assess body adiposity index (BAI) and associated factors in workers of the furniture sector. A descriptive study was conducted with 204 workers of the furniture sector in the city of Ubá-MG of both sexes aged 20-70 years. Working sector, economic class, level of physical activity, body mass index, waist circumference, abdominal circumference, waist-to-hip ratio, systolic and diastolic blood pressure, fasting glycemia, total cholesterol, high density lipoprotein, low density lipoprotein and triglycerides were assessed. Odds ratio (RC) was used to determine the strength of as- sociation among variables. Of the total number of individuals assessed, 50% had high BAI, presenting higher anthropometric, blood pressure, glucose and triglyceride values (p <0.05). It was observed that advanced age (RC: 2.76; p = 0.002) and production sector (RC: 2.52; p = 0.045) were significantly associated with BAI.
    [Show full text]
  • Body Adiposity Index Is Worse Than Body Mass Index When Eval
    ISSN: 2469-5858 Fogal et al. J Geriatr Med Gerontol 2017, 3:035 DOI: 10.23937/2469-5858/1510035 Volume 3 | Issue 4 Journal of Open Access Geriatric Medicine and Gerontology RESEARCH ARTICLE Body Adiposity Index is Worse than Body Mass Index when Eval- uating the Factors Associated with Adiposity in Elderly People Aline Siqueira Fogal, Sylvia do Carmo Castro Franceschini, Giana Zarbato Longo and Andréia Queiroz Ribeiro* Departamento de Nutrição, Universidade Federal de Viçosa, Viçosa, Brazil *Corresponding authors: Andréia Queiroz Ribeiro, Professor Adjunto IV, Departamento de Nutrição e Check for Saúde, Universidade Federal de Viçosa, Brazil, E-mail: [email protected] updates Abstract Introduction Background: Body Mass Index (BMI) is an easily measurable In the elderly, obesity is associated with accelerated indicator of body fat and with low cost. However, as an indicator loss of cognitive function, frailty and functional disabil- of risk of development of chronic diseases in the elderly, it has ity and premature death from Cardiovascular Disease limitations, as it does not reflect mainly the regional distribution of fat that occurs with the aging process. As an alternative to (CVD), diabetes, cancer and musculoskeletal diseas- BMI, the Body Adiposity Index (BAI) has been proposed. This es and other chronic non-communicable diseases [1]. index showed a high correlation with the measurement of body These diseases affect both quality of life and longevity fat in adults indicating that it could replace BMI. However, BAI and generate high costs to health systems. is still understudied in the elderly. Due to the accelerated process of population aging Objective: To determine factors associated with adiposity in elderly people, according to sex and in accordance with two in the world and the concomitant increase in the prev- anthropometric indices, Body Mass Index (BMI) and Body Ad- alence of overweight and obesity, it is necessary to in- iposity Index (BAI).
    [Show full text]
  • Comparative Assessment of Methods for Determining Adiposity and a Model for Obesity Index
    bioRxiv preprint doi: https://doi.org/10.1101/710970; this version posted July 22, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY 4.0 International license. 1 Title 2 Comparative assessment of methods for determining adiposity and a model for 3 obesity index 4 5 Running title: 6 Indices for assessment and modelling of obesity 7 8 David Adedia1, Adjoa A. Boakye2, Daniel Mensah3, Sylvester Y. Lokpo4, Innocent Afeke4, Kwabena O. 9 Duedu2* 10 1 Department of Basic Sciences, School of Basic & Biomedical Sciences, University of Health and 11 Allied Sciences, Ho, Ghana 12 2 Department of Biomedical Sciences, School of Basic & Biomedical Sciences, University of Health 13 and Allied Sciences, Ho, Ghana 14 3 Department of Nutrition and Dietetics, School of Allied Health Sciences, University of Health and 15 Allied Sciences, Ho, Ghana 16 4 Department of Medical Laboratory Sciences, School of Allied Health Sciences, University of Health 17 and Allied Sciences, Ho, Ghana 18 19 *Corresponding Author: Department of Biomedical Sciences, University of Health and Allied Sciences, 20 PMB 31. Ho VH-0194-2524. Ghana. 21 Email: [email protected] or [email protected] Tel: +233545017098 22 23 24 Competing Interests: No competing interests declared. The African Partnership for Chronic 25 Disease Research (APCDR), Cambridge, UK provided postdoctoral fellowship funding to 26 KOD. 1 bioRxiv preprint doi: https://doi.org/10.1101/710970; this version posted July 22, 2019.
    [Show full text]
  • Visceral Adiposity in Relation to Body Adiposity and Nutritional Status in Elderly Patients with Stable Coronary Artery Disease
    nutrients Article Visceral Adiposity in Relation to Body Adiposity and Nutritional Status in Elderly Patients with Stable Coronary Artery Disease Bartosz Hudzik 1,2,* , Justyna Nowak 1, Janusz Szkodzi ´nski 2 and Barbara Zubelewicz-Szkodzi ´nska 3,4 1 Department of Cardiovascular Disease Prevention, Department of Metabolic Disease Prevention, Faculty of Health Sciences, Medical University of Silesia, 41-902 Bytom, Poland; [email protected] 2 Third Department of Cardiology, Silesian Center for Heart Disease, Faculty of Medical Sciences, Medical University of Silesia, 41-800 Zabrze, Poland; [email protected] 3 Department of Nutrition-Related Disease Prevention, Department of Metabolic Disease Prevention, Faculty of Health Sciences, Medical University of Silesia, 41-902 Bytom, Poland; [email protected] 4 Department of Endocrinology, District Hospital, 41-940 Piekary Sl´ ˛askie,Poland * Correspondence: [email protected] Abstract: Introduction: The accumulation of visceral abdominal tissue (VAT) seems to be a hallmark feature of abdominal obesity and substantially contributes to metabolic abnormalities. There are numerous factors that make the body-mass index (BMI) a suboptimal measure of adiposity. The visceral adiposity index (VAI) may be considered a simple surrogate marker of visceral adipose tissue dysfunction. However, the evidence comparing general to visceral adiposity in CAD is scarce. Therefore, we have set out to investigate visceral adiposity in relation to general adiposity in patients Citation: Hudzik, B.; Nowak, J.; with stable CAD. Material and methods: A total of 204 patients with stable CAD hospitalized in Szkodzi´nski,J.; Zubelewicz- the Department of Medicine and the Department of Geriatrics entered the study. Based on the Szkodzi´nska,B.
    [Show full text]
  • Body Adiposity Index Versus Body Mass Index and Other Anthropometric Traits As Correlates of Cardiometabolic Risk Factors
    Body Adiposity Index versus Body Mass Index and Other Anthropometric Traits as Correlates of Cardiometabolic Risk Factors Charlene T. Lichtash1, Jinrui Cui2, Xiuqing Guo2, Yii-Der I. Chen2, Willa A. Hsueh3, Jerome I. Rotter1,2, Mark O. Goodarzi1,2,4,5* 1 Department of Medicine, Cedars-Sinai Medical Center, Los Angeles, California, United States of America, 2 Medical Genetics Institute, Cedars-Sinai Medical Center, Los Angeles, California, United States of America, 3 Diabetes Research Center, Division of Diabetes, Obesity and Lipids, Methodist Hospital Research Institute, Houston, Texas, United States of America, 4 Division of Endocrinology, Diabetes and Metabolism, Cedars-Sinai Medical Center, Los Angeles, California, United States of America, 5 Department of Medicine, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California, United States of America Abstract Objective: The worldwide prevalence of obesity mandates a widely accessible tool to categorize adiposity that can best predict associated health risks. The body adiposity index (BAI) was designed as a single equation to predict body adiposity in pooled analysis of both genders. We compared body adiposity index (BAI), body mass index (BMI), and other anthropometric measures, including percent body fat (PBF), in their correlations with cardiometabolic risk factors. We also compared BAI with BMI to determine which index is a better predictor of PBF. Methods: The cohort consisted of 698 Mexican Americans. We calculated correlations of BAI, BMI, and other anthropometric measurements (PBF measured by dual energy X-ray absorptiometry, waist and hip circumference, height, weight) with glucose homeostasis indices (including insulin sensitivity and insulin clearance from euglycemic clamp), lipid parameters, cardiovascular traits (including carotid intima-media thickness), and biomarkers (C-reactive protein, plasminogen activator inhibitor-1 and adiponectin).
    [Show full text]
  • Comparison of the Body Adiposity Index to Body Mass Index in Korean Women
    http://dx.doi.org/10.3349/ymj.2014.55.4.1028 Original Article pISSN: 0513-5796, eISSN: 1976-2437 Yonsei Med J 55(4):1028-1035, 2014 Comparison of the Body Adiposity Index to Body Mass Index in Korean Women Yeon-Ah Sung, Jee-Young Oh, and Hyejin Lee Department of Internal Medicine, Ewha Womans University School of Medicine, Seoul, Korea. Received: August 30, 2013 Purpose: Obesity is a major public health issue and is associated with many meta- Revised: November 13, 2013 bolic abnormalities. Consequently, the assessment of obesity is very important. A Accepted: November 25, 2013 new measurement, the body adiposity index (BAI), has recently been proposed to Corresponding author: Dr. Hyejin Lee, provide valid estimates of body fat percentages. The objective of this study was to Department of Internal Medicine, compare the BAI and body mass index (BMI) as measurements of body adiposity Ewha Womans University School of Medicine, Ewha Womans University Mokdong Hospital, and metabolic risk. Materials and Methods: This was a cross-sectional analysis 1071 Anyangcheon-ro, Yangcheon-gu, performed on Korean women. The weight, height, and hip circumferences of 2950 Seoul 158-710, Korea. women (mean age 25±5 years old, 18--39 years) were measured, and their BMI Tel: 82-10-2650-2846, Fax: 82-2-2650-2846 and BAI [hip circumference (cm)/height (m)1.5-18] values were calculated. Bio- E-mail: [email protected] electric impedance analysis was used to evaluate body fat content. Glucose toler- ∙ The authors have no financial conflicts of ance status was assessed with a 75-g oral glucose tolerance test, and insulin sensi- interest.
    [Show full text]
  • Associations Between Adiposity Indicators and Elevated Blood Pressure Among Chinese Children and Adolescents
    Journal of Human Hypertension (2015) 29, 236–240 © 2015 Macmillan Publishers Limited All rights reserved 0950-9240/15 www.nature.com/jhh ORIGINAL ARTICLE Associations between adiposity indicators and elevated blood pressure among Chinese children and adolescents B Dong1,2, Z Wang1,2, H-J Wang1 and J Ma1 Adiposity is closely related to elevated blood pressure (BP); however, which adiposity indicator is the best predictor of elevated BP among children and adolescents is unclear. To clarify this, 99 366 participants aged 7–17 years from the Chinese National Survey on Students’ Constitution and Health in 2010 were included in this study. The adiposity indicators, including weight, body mass index (BMI), waist circumference, waist-to-height ratio (WHtR), hip circumference, body adiposity index (BAI), waist-to-hip ratio (WHR) and skinfold thickness, were converted into z-scores before use. The associations between elevated BP and adiposity indicators z-scores were assessed by using logistic regression model and area under the receiver operating characteristic curve (AUC). In general, BAI, BMI and WHtR z-scores were superior for predicting elevated BP compared with weight, waist circumference, hip circumference, WHR and skinfold thickness z-scores. In both sexes, BMI z-score revealed slightly higher AUCs than other indicators. Our findings suggest that general adiposity indicators were equivalent, if not superior, to abdominal adiposity indicators to predict elevated BP. BMI could be a better predictor of elevated BP than other studied adiposity indicators in children. Journal of Human Hypertension (2015) 29, 236–240; doi:10.1038/jhh.2014.95; published online 23 October 2014 INTRODUCTION the performance of this index for predicting elevated BP in Hypertension is the leading risk factor for cardiovascular disease children has not been assessed.
    [Show full text]
  • Índice De Masa Corporal (IMC), IMC Ajustado a La Grasa, Índice De Adiposidad (IA) E IA Ajustado (Baifels).¿ Cuál Es El Mejor Índice De Adiposidad Para Detectar El Exceso De Peso?
    Nutr Hosp. 2017; 34(2):389-395 ISSN 0212-1611 - CODEN NUHOEQ S.V.R. 318 Nutrición Hospitalaria Trabajo Original Valoración nutricional BMI, BMIfat, BAI or BAIFels – Which is the best adiposity index for the detection of excess weight? Índice de masa corporal (IMC), IMC ajustado a la grasa, índice de adiposidad (IA) e IA ajustado (BaIFels). ¿Cuál es el mejor índice de adiposidad para detectar el exceso de peso? Bruna Ramos Silva1, Mirele Savegnago Mialich1, Daniel J. Hoffman2 and Alceu Afonso Jordao Junior1 1Department of Internal Medicine. Ribeirao Preto Medical School. University of Sao Paulo. Ribeirao Preto, SP. Brazil. 2Department of Nutritional Sciences. Rutgers University. New Brunswick, New Jersey. USA Abstract Objective: To compare the diagnostic performance of adiposity indeces body mass index (BMI), body mass index adjusted for fat mass (BMIfat), body adiposity index (BAI) and body adiposity index for the Fels Longitudinal Study sample (BAIFels) and the overweight detection in a sample of the Brazilian population. Methods: Cross-sectional study with 501 individuals (female/male = 387/114), which underwent anthropometric measurements and body composition for subsequent calculation of adiposity indices. Statistical analyzes considered p < 0.05 as statistically signifi cant. Results: The averages were: age of 46.94 ± 14.22 years and 48.05 ± 14.40 years, weight 79.5 ± 16, 14 kg and 70.42 ± 16,62 kg, height 172.86 ± 7.6 cm and 159.0 ± 7,35 cm, for men and women, respectively. According to the eutrophic ratings and overweight, the BMIfat ranked 40.3% and 34.0% for men and 21.7% and 65.0% for females, respectively.
    [Show full text]
  • Body Adiposity Index and Associated Factors in Adults: Method and Logistics of a Population-Based Study
    Nutr Hosp. 2015;32(1):101-109 ISSN 0212-1611 • CODEN NUHOEQ S.V.R. 318 Original / Obesidad Body adiposity index and associated factors in adults: method and logistics of a population-based study Wellington Segheto1, Danielle Cristina Guimarães da Silva1, France Araújo Coelho1, Vanessa Guimaraes Reis1, Sílvia Helena Oliveira Morais1, João Carlos Bouzas Marins2, Andréia Queiroz Ribeiro3 and Giana Zarbato Longo3 1Federal University of Viçosa, Minas Gerais. 2Department of Physical Education and Sports. Federal University of Viçosa, Minas Gerais. 3Nutrition and Health Department. Federal University of Viçosa, Minas Gerais, Brazil. Abstract ÍNDICE DE ADIPOSIDAD CORPORAL Y FACTORES ASOCIADOS EN ADULTOS: Introduction: obesity is a public health problem that MÉTODO Y LOGÍSTICA DE UN ESTUDIO has increased considerably. Several techniques have been POBLACIONAL developed and used to measure the amount of body fat, or a combination of excess fat with some comorbidities. The Body Adiposity Index is a new method proposed to Resumen determine body fat and its validation is still limited. Me- Introducción: la obesidad es un problema de salud pú- thods and logistics of a population-based study reported blica que ha aumentado considerablemente. Se han desa- in the literature are few, mainly multidiciplinas team. rrollado distintas técnicas para medir la cantidad de grasa Objective: the objective was to report the proceedings corporal, o una combinación de exceso de grasa con ciertas of a population-based study, the denouement is the index comorbilidades. El Índice de Adiposidad Corporal es un of adiposity in adults. nuevo método propuesto para determinar la grasa corporal Design: the design of this study was cross-sectional, y su validación es aún limitada.
    [Show full text]